Duck gait: Relationship to hip angle, bone ash, bone density, and morphology Cara I. Robison,∗ Meredith Rice,∗ Maja M. Makagon,† and Darrin M. Karcher∗,1 ∗
Department of Animal Science, Michigan State University, East Lansing, MI; and † Department of Animal Sciences, Purdue University, West Lafayette, IN
ABSTRACT The rapid growth meat birds, including ducks, undergo requires skeletal integrity; however, fast growth may not be conducive to adequate bone structure. A relationship likely exists between skeletal changes and duck mobility. Reduced mobility in meat ducks may have impacts on welfare and production. This study examined the relationships among gait score, bone parameters, and hip angle. Commercial Pekin ducks, ages 14 d (n = 100), 21 d (n = 100), and 32 d (n = 100) were weighed and gait scored with a 3-point gait score system by an observer as they walked over a Tekscan gait analysis system. Gait was scored as GS0, GS1, or GS2 with a score of GS0 defined as good walking ability and a score of GS2 as poorest walking ability. Ducks were humanely euthanized, full body scanned using quantitative computed tomography (QCT), and the right femur and tibia were extracted. Leg bones were cleaned, measured, fat extracted, and ashed. QCT scans were rendered to create computer-
ized 3D models where pelvic hip angles and bone density were measured. Statistical analysis was conducted using PROC MIXED with age and gait score in the model. Body weight increased with age, but within an age, body weight decreased as walking ability became worse (P < 0.01). As expected, linear increases in tibia and femur bone width and length were observed as the ducks aged (P < 0.01). Right and left hip angle increased with duck age (P < 0.01). Additionally, ducks with a GS2 had wider hip angles opposed to ducks with a GS0 (P < 0.01). Bone density increased linearly with both age and gait score (P < 0.05). Femur ash content was lowest in 32-day-old ducks and ducks with GS1 and GS2 (P < 0.0001). Tibia ash content increased with age, but decreased as gait score increased (P < 0.001). The observation that right hip angle changed with gait scores merits further investigation into the relationship between duck mobility and skeletal changes during growth.
Key words: Pekin duck, gait score, bone ash, tibia, femur 2015 Poultry Science 94:1060–1067 http://dx.doi.org/10.3382/ps/pev050
INTRODUCTION Broiler chickens and turkeys are more commonly studied with less attention given to ducks. Irrespective of the species, meat birds have been genetically selected for breast yield resulting in an increased body weight that puts stress on the immature skeleton and can cause a variety of skeletal deformities and disorders (Lilburn, 1994; Brickett et al., 2007). Some of these bone abnormalities include tibial dyschondroplasia, osteomyelitis, bone fractures, and abnormal bone deformation (Orth and Cook, 1994; Charuta et al., 2011; Wideman et al., 2014). These disorders can lead to poor gait, lameness, and eventual culling from the population, resulting in poor animal well-being and product loss. Gait has been studied at length in broilers and turkeys using multiple gait scoring systems (Abourachid, 1991; Kestin et al., 1992; Webster et al., C 2015 Poultry Science Association Inc. Received September 3, 2014. Accepted December 3, 2014. 1 Corresponding author: [email protected]
2008). Kestin et al. (1992) developed a gait scoring system that was modified and adapted for use in ducks (Jones and Dawkins, 2010; O’Driscoll and Broom, 2011). Karcher et al. (2013) reported concern over the accurate assessment using the Jones and Dawkins (2010) modified duck gait scoring system due to the possibility of the natural fear response masking lameness. Additionally, the differences in musculoskeletal development and gait in ducks compared to chickens and turkeys raises concerns over the method’s appropriateness. Therefore, there is a need for research that explores the accuracy of the system, for example by assessing the relationship between gait score and physiological parameters. Sound structural conformation is a main contributor to successful locomotion and poor conformation may be conducive to lameness in ducks. To date only a few studies have attempted to address and quantify the relationships between gait and skeletal structural characteristics in ducks. The duck is considered to be a nonspecialist walker with a suboptimal walking gait. Compared to the gait of specialist walkers, the waddle
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has a high cost of locomotion as well as alterations in biomechanics. In order to waddle the duck must shift, tilt, and rotate its body to bring the center of mass over the stance leg (Nudds et al., 2010). Rylander and Bolen (1974) conducted a study comparing gait alterations in different species of whistling ducks. The cursorial species, adapted for running, had a greater hip angle and less angular displacement than the swimming species. This is likely a reflection of evolutionary adaptations to different habitats. Therefore, changes in the angular displacement of the hip were reflected as a change in gait. Skeletal assessment, including bone angulation, can be accomplished through computed tomography (CT), (Korver et al., 2004; Van Wyhe et al., 2014; Regmi et al., 2015) bone ashing (Brickett et al., 2007; Van Wyhe et al., 2012; Zhong et al., 2012), and physical observation. These methods allow measurements of morphological and skeletal parameters to determine what parameters may influence changes in walking ability. The purpose of our study was to evaluate the correlations between walking ability and skeletal parameters to determine whether alterations in hip angle, leg length, and bone characteristics have an impact on walking ability in commercial Pekin ducks.
MATERIALS AND METHODS All procedures were approved by the Institutional Animal Care and Use Committee of Michigan State University. On-farm data was collected on commercial duck farms located in northern Indiana. As part of a larger gait study, the walking abilities of 966 commercial Pekin ducks were assessed at 13 to 14 (14 d; 248 ducks), 20 to 21 (21 d; 350 ducks) and 30 to 32 (31 d; 368 ducks) d age. The ducks were selected from across 11 flocks housed in 7 different barns. Makagon et al. describes in detail the setup for assessing gait and descriptions for each gait score category. In order to have a balanced data set, ducks with each gait score were targeted and therefore, the data set does not mimic the distribution of each gait score in the population. Briefly, ducks were weighed, gender-identified, and walked through a tunnel containing a Tekscan gait analysis pad (Tekscan HRV2 High Resolution Animal Walkway System, Tekscan, Inc., South Boston, MA) to collect foot pad pressure, gait cadence, and velocity data. The ducks were videotaped from the anterior as they waddled through the tunnel. Simultaneously, a trained observer assigned each duck a gait score from “0” (GS0; best gait) to “2” (GS2; poor gait). A subsample of ducks was selected from the larger sample for skeletal analysis. To ensure that a representative sample of ducks with the 3 gait score categories was assessed, a minimum of 10 ducks with each score was selected from each age to be analyzed for skeletal parameters. An additional 80 ducks per age group were randomly selected for a total of 100 ducks per age (Table 1). These ducks
Table 1. Sample size distribution of ducks analyzed for each age by gait combination. Gait Score Age (d)
0
1
2
Total (n)
14 21 32
37 33 37
35 33 30
28 34 33
100 100 100
were CO2 euthanized, tagged for identification, placed on ice, and transported to Michigan State University for further analysis. All ducks were placed on their backs in dorsal recumbency with their legs out straight to rigor.
Computed Tomography and Necropsies Full-body scans of the ducks were done using a 16slice, GE Brightspeed quantitative computed tomography (QCT) scanner (General Electric Healthcare, Princeton, NJ) at the Michigan State University Veterinary Teaching Hospital. All ducks were allowed to go through rigor mortis in the same position prior to QCT scanning. Ducks were laid on the scanner board positioned in dorsal recumbency and scanned with a calibration phantom (Image Analysis, Inc., Columbia, KY) containing various concentrations of calcium hydroxyapatite. Bone lengths, bone density, leg length, and hip angles were analyzed from the scans using Mimics Innovation Software version 16.0 (Materialise, Plymouth, MI). Mimics Innovation Software measures density in Hounsfield units. During bone density analysis a linear regression line was created graphing the known values of mg Ca/cm3 , contained within the calibration phantom, against density of the phantom in Hounsfield units acquired from Mimics. The resulting linear equation was used to quantify the bone density measurements. The ends of the tarsometatarsus, tibia, and femur in each leg were located and the length from the distal end of the tarsometarasus to the distal end of the femur was measured. Then the distance from the distal end of the femur to the acetabulum was measured. Total leg length was measured as a summation of the length of the long bones plus the joint space from the acetabulum to the distal end of the tarsometatarsus. Hip angles were determined by measuring the midpoint of the distal end of the femur to the center of the acetabulum and then to the distal end of the pubis. The cross-sectional image slice at the midpoint of the right and left tibia and femur was measured to produce an average cortical bone density (CBD). Ducks were necropsied at the Diagnostic Center for Population and Animal Health where the right femur and tibia were removed. The leg bones were taken back to the lab and cleaned of surrounding muscles and soft tissues. The tibia and femur length were measured using a metric ruler, and bone width was determined with digital calipers (Model 68304, Pittsburgh, Camarillo,
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CA). The fibula was removed from the tibia and both tibia and femur were cut into pieces to enhance fat extraction, wrapped in cheesecloth, and placed into a soxhlet for ether extraction. After ether extraction, the bone pieces were weighed into crucibles for dry matter and ash. The bone pieces were dried at 105◦ C for 24 h in an American Scientific DN-81 constant temperature oven (Portland, OR). Bones were then placed in the ash oven (Thermolyne, 30400, Barnstead International, Dubuque, IA) at 600◦ C for 8 h. The ashed bone pieces were again weighed and ash percentage was determined.
Statistics Data were analyzed by using the PROC MIXED analysis of SAS 9.3 (SAS Institute, Cary, NC). The class variables were defined as age and gait. The main effects of age, gait score, and age by gait interactions were examined. Differences between means for age, gait score, and age by gait interactions were tested using Tukey’s adjustment with significance accepted at P < 0.05. In order to facilitate the interpretation of significant age by gait interactions, those data are presented graphically. Linear and quadratic contrasts were calculated for age and gait with significance considered at P < 0.05. Additionally, correlations were calculated between dependent variables to determine collinearity. Body weight was not used as a covariate for statistical analysis due to its strong correlation with the independent variables.
RESULTS AND DISCUSSION A duck’s ambulatory ability can have a negative impact on well-being and reduce producer profitability.
The reduced walking ability might translate to decreased growth potential or result in the duck being culled in severe cases. In broilers, Kestin et al. (1992) developed a scoring system to evaluate gait finding a relationship between body weight and leg weakness. Figure 1 presents the body weight of ducks at 14, 21, and 32 d age. As expected, body weight increased as the ducks aged (P < 0.01); however, the average body weight within a specific age decreased linearly as gait score worsened (P < 0.01). Talaty et al. (2010) reported broilers with poor walking ability, scores of 4 and 5 on a scale of 0 to 5, had decreased mobility and trouble accessing feeders and waterers resulting in lower body weights. However, Weeks et al. (2000) reported that broilers with poor walking ability made fewer visits to the feeder, but concomitantly increased the time spent at the feeder resulting in similar amounts of feed consumed to broilers with better walking ability. Therefore, the observation of a decreased average body weight of 0.5 kg at 32 d (Figure 1) between GS0 and the other gait scores could be a result of decreased mobility. This may have resulted in unsuccessful access to feed and water but this is a speculation, as resource usage was not evaluated. The Mimics Software provided analysis of bone structure in the 3D view to measure hip angulation as well as total leg length with main effects of age and gait score (Figure 2; Tables 2 and 3). In the current study, the use of QCT provided a novel approach, but also challenges. The ducks could not be scanned in a natural position, therefore a dorsal position with the legs and hips in a neutral position was chosen. However, the positioning of the duck on the CT scanner and human measurement error could alter the angles measured. The results revealed that right and left hip angle increased
Figure 1. Average body weight (kg) of 14, 21, and 32-day-old ducks by gait score. There was an overall age × gait score interaction (P < 0.01) and within each age group body weight decreased linearly as gait score increased (P < 0.01). Bars with differing letters within a given age designate differences between gait score P < 0.05.
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Figure 2. Three-dimentional image created from a QCT scan by Mimics Innovation Software version 16.0 (Materialise, Plymouth, MI) of the distal half of a duck’s skeleton.
with duck age (Table 2; P < 0.03) and the calculated difference between right and left hip angles increased from 0.33 degrees for ducks with GS0 to 3.04 degrees for ducks with GS2 (Table 3; P < 0.005). A main effect interaction was observed for right hip angle finding ducks within an age with gait scores of 1 and 2 had wider hip angles opposed to ducks with a gait score of 0 (Figure 3, P = 0.03). Rylander and Bolen (1974) conducted gait analysis of four different species of whistling ducks and showed differences in the angular displacement of the hip. In the
aforementioned study, hip angulation was measured using a series of 2D still images and measurements from preserved specimens to estimate bone length and position. Rylander and Bolen (1974) used the anterior ilium, acetabulum, and femur to look at hip angle because they were interested in how hip angle was affected by changes in vertical posture. In the current study, the focus was placed on how the walking ability is affected by hip angle, therefore it was important to include leg abduction so the distal pubis was used in place of the ilium to create the hip angle. Additionally, with the
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ROBISON ET AL. Table 2. Commercial Pekin duck skeletal parameter means at 3 different ages during a production period. Age Variable
14 d
Source of Variation
21 d
(P-value)1
32 d
Femur Dry weight (g) Ash (%) Length (cm) Width (mm)
1.28 47.52 4.88 4.89
± ± ± ±
0.05c 0.31a 0.04c 0.06c
2.28 48.30 5.92 5.94
± ± ± ±
0.05b 0.31a 0.04b 0.06b
3.85 46.36 6.90 6.90
± ± ± ±
0.05a 0.3b 0.04a 0.06a
< 0.0001 < 0.0001 < 0.0001 < 0.0001
Tibia Dry weight (g) Ash (%) Length (cm) Width (mm)
2.08 49.66 7.83 4.64
± ± ± ±
0.08c 0.34a 0.07c 0.07c
3.94 50.93 9.54 5.74
± ± ± ±
0.08b 0.34b 0.07b 0.07b
6.65 51.63 11.24 7.16
± ± ± ±
0.08a 0.34b 0.07a 0.07a
< 0.0001 0.0002 < 0.0001 < 0.0001
Hip angle (degree) Right Left Leg length (cm) Right Left Density (mg Ca/cm3 ) Right femur Left femur Right tibia Left tibia 1
71.52 ± 1.16b 69.56 ± 1.24b
72.98 ± 1.14a,b 71.18 ± 1.22a,b
75.79 ± 1.16a 75.18 ± 1.24a
0.03 0.005
17.71 ± 0.14c 17.58 ± 0.14c
20.61 ± 0.14b 20.63 ± 0.14b
23.75 ± 0.14a 23.79 ± 0.14a
< 0.0001 < 0.0001
± ± ± ±
< 0.0001 < 0.0001 < 0.0001 < 0.0001
460.90 451.59 435.35 433.95
± ± ± ±
10.14c 10.30b 11.06c 11.24c
501.74 518.82 482.35 491.97
± ± ± ±
10.07b 10.30a 10.99b 11.73b
552.21 540.90 550.80 541.75
10.29a 10.38a 11.10a 11.96a
Age main effect P-value. Different superscripts in a row designate significant differences between ages; P < 0.05.
a–c
Table 3. Commercial Pekin duck skeletal parameter means of 3 different gait scores assessed at 14, 21, and 32 d during a production period. Gait Score Variable
0
1
Source of Variation (P-value)1
2
Femur Dry weight (g) Ash (%) Length (cm) Width (mm)
2.48 48.63 5.92 5.92
± ± ± ±
0.04 0.30a 0.04 0.06
2.49 46.93 5.93 5.88
± ± ± ±
0.05 0.31b 0.04 0.06
2.43 46.61 5.84 5.94
± ± ± ±
0.05 0.32b 0.041 0.062
0.70 < 0.0001 0.24 0.77
Tibia Dry weight (g) Ash (%) Length (cm) Width (mm)
4.36 51.61 9.66 5.95
± ± ± ±
0.07 0.33a 0.07a 0.07
4.14 50.76 9.54 5.73
± ± ± ±
0.08 0.34a,b 0.07a,b 0.07
4.17 49.84 9.40 5.87
± ± ± ±
0.08 0.35b 0.07b 0.08
0.09 0.002 0.03 0.12
Hip angle (degree) Right Left
69.89 ± 1.12b 69.48 ± 1.20b
72.36 ± 1.16b 71.30 ± 1.25a,b
78.29 ± 1.19a 75.14 ± 1.26a
< 0.001 0.005
Leg length (cm) Right Left
21.14 ± 0.13a 21.14 ± 0.14a
20.58 ± 0.14b 20.59 ± 0.14b
20.35 ± 0.14b 20.26 ± 0.15b
0.0002 < 0.0001
± ± ± ±
0.005 0.0002 0.06 0.0027
Density (mg Ca/cm3 ) Right femur Left femur Right tibia Left tibia 1
479.93 476.89 474.95 463.25
± ± ± ±
9.76b 9.90b 10.59 11.24b
508.27 497.73 482.93 484.55
± ± ± ±
10.29a,b 10.46b 11.19 11.73a,b
526.23 536.69 510.63 519.87
10.44a 10.58a 11.37 11.96a
Gait main effect P-value. Different superscripts in a row designate significant differences between gait scores; P < 0.05.
a,b
ducks in a dorsal recumbancy position the angle using the ilium would have been distorted by positioning. Campbell et al. (2014) reported that in Pekin ducks metatarsal adduction was greater in the right pelvic limb compared to the left especially at 28 d; however, all ducks showed signs of metatarsal adduction suggest-
ing that it may be normal. Duff (1984) reported that turkeys with severe degenerative hip disease walked with an abnormal gait and stood and walked with abducted limbs possibly as a result of the disease. Biomechanical analysis of avian locomotion in guinea fowl demonstrated that a small change in the long angle
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Figure 3. Right hip angle (deg) of 14, 21, and 32-day-old ducks by gait score. There was an overall age × gait score interaction (P < 0.05) and within each age group hip angle increased linearly as gait score increased (P < 0.01). Bars with differing letters within a given age designate differences between gait score P < 0.05.
rotation of the hip could result in a relatively large distal displacement of the lower limb (Kambic et al., 2014). Hip angle in the current study was measured while the duck was in dorsal recumbency, an atypical position; however, if the changes in gait were chronic then alterations in musculature may also have occurred allowing measurable differences even in an atypical position. In future studies, it would be interesting to take still photos of the bird’s stance to compare to the 3D images from the CT scans. The increased hip angle observed in the current study might suggest increased metatarsal abduction resulting in a reluctance to rotate the leg completely under the center of mass during the stance phase. In addition to a change in the swing path of the leg, hip abduction widens the stance of the bird, which may alleviate pressure on an injured or sore limb. This would require further investigation. Leg length was measured as a summation of the length of the long bones plus the joint space from the acetabulum to the distal end of the tarsometatarsus. The joint space inclusion in measuring leg length would account for inflammation and swelling. In a human study on knee osteoarthritis, leg length was measured from the femoral head to the distal end of the tibia. In that study, patients with a leg length difference of 1 cm or greater had a 53% higher chance of having radiographic knee osteoarthritis in the shorter leg (Harvey, 2010). Right and left leg lengths were increased with duck age (Table 2; P < 0.0001). Conversely, the leg lengths decreased with increasing gait score (Table 3; P < 0.002). The decreasing leg length associated with gait score might be due to a smaller size of the bird, or be reflective of a fractured and remodeled tibia. During the 3D analysis, researchers observed that some leg
bones had remodeled fractures and that a large percentage of the ducks had tibias with a noticeable wave to the diaphyseal region; however, this information was not quantified. The tibia itself remained straight, but the cortical bone was modeled to give a wavy look to the bone. The rendering, or creation of the 3D image, of the bone may have had an overall impact on leg length, but when the femur and tibia were measured, length and width increased with age (Table 2; P < 0.0001) while tibia length decreased with increasing gait score (Table 3; P < 0.02). Therefore, the changes observed in leg length between 0 and 2 gait scored ducks were likely not impacted by the rendering. Rapid growth rate in meat birds has been suggested to be the main contributor to inadequate bone quality (Williams et al., 2004). Bone quality consists of the architectural organization as well as the organic and mineral matrices (Rath et al., 2000). Bone ash is a measure of the mineral content of the bone, primarily consisting of Ca and P. The inorganic matrix constitutes 60 to 70% of the bone weight providing bone weight and strength (Rath et al., 2000). The ash content of the femur was lowest in 32 d old ducks and ducks with gait scores of 1 and 2 (Tables 2, 3; P < 0.0001). Tibia ash content increased with age, but decreased as gait score became worse (Tables 2, 3; P < 0.001). A recent publication compared the bone ash of duck femurs and tibias from years 2010 and 1993 flocks (Van Wyhe et al., 2012). Although bone ash is reported as epiphyseal and diaphyseal ash, whole bone ash could be estimated as the average between the 2 measurements. Van Wyhe et al. (2012) reported tibia ash at 60% in the tibial diaphysis and 37% in the epiphysis, averaging to approximately 48.5% in 32-day-old year 2010 ducks, which is comparable to the 51% reported in the current study.
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Similarly, the femur ash measurement would average to approximately 49% in 32-day-old year 2010 ducks, which compares to the 46% reported in the current study. In addition to bone mineral content, bone density, defined as the mass of material per volume of bone (Rath et al., 2000), also provides valuable information on the quality of bone as it mirrors the status of bone health (Rath et al., 2000). Computed tomography has previously been used to determine volumetric bone mineral density (vBMD) and content in bones from turkeys and ducks (Charuta et al., 2012; Charuta and Cooper, 2012). In the current study, average bone density was measured at the midpoint of the tibia or femur in both the right and left leg. As expected, all density measurements increased linearly as the ducks aged (Table 2; P < 0.01). Table 3 reports the bone density for each gait score finding that as gait score increases so does the density (P < 0.005). This would suggest that as the duck ages the leg bones begin to undergo bi-lateral changes in bone density likely due to alterations in gait. Research conducted in French Pekin ducks with a 56 d slaughtering maturity reported higher vBMD at the middle of the diaphysis of the tibiotarsal bone at both 14 and 28 d (∼625 mg/cm3 ; Charuta et al., 2012). Fourteen-day-old ducks had vBMD of 435 mg/cm3 and 32-day-old ducks had a vBMD of 540 mg/cm3 (Table 2). The ducks in the current study have been selected for a 36 d slaughtering maturity and were heavier than the French ducks at both time points. Therefore, the authors speculate that the combination of increased body weight coupled with reduced vBMD could predispose bone to fractures as the duck reaches its physiological limit on the quantity and quality of bone it can produce. The ability to create 3D models of the skeleton from the QCT scans of an intact duck provides the opportunity to measure joint angulation and skeletal structure, and offers insight into the skeletal development of the Pekin duck. The rapid growth Pekin ducks experience in a short time frame requires sufficient skeletal integrity to ensure mobility. The increase in body weight, leg length, and bone density was expected since the ducks are growing. The interesting observations made between a decreased leg length, increased bone density, and increased right hip angle related to higher gait scores require further examination of these specific variables. Further studies involving muscular development, skeletal health (e.g. osteomyelitis), and skeletal injury (e.g., fractures) also need to be conducted to determine the impact on gait score. A refined understanding of the complex relationship between management practices, skeletal parameters, and gait score will then allow for duck well-being to be better understood.
ACKNOWLEDGMENTS We gratefully acknowledge Maple Leaf Farms, Inc. (Leesburg, IN) for generously providing resources for this study, and particularly Michael Turk and Daniel
Shafer for supporting this study. We thank Chad Risch (Maple Leaf Farms, Inc.) and Stephanie Robles (Purdue University) for overseeing and assisting with onfarm data collection. For assistance in various phases of data collection we thank: Prafulla Regmi, Robert Van Wyhe, Kailynn Van de Water, Natalie Smith, Diondra Voisch, and Lachelle Devoe from Michigan State University; and Luna KC, Kayla Winemiller, and Danyi Ma from Purdue University.
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AN ANALYSIS OF DUCK GAIT Orth, M. W., and M. E. Cook. 1994. Avian tibial dyschondroplasia: A morphological and biochemical review of the growth plate lesion and its causes. Vet. Path. 31:403–414. Rath, N., G. Huff, W. Huff, and J. Balog. 2000. Factors regulating bone maturity and strength in poultry. Poult. Sci. 79:1024– 1032. Regmi, P., T. S. Deland, J. P. Steibel, C. I. Robison, R. C. Haut, M. W. Orth, and D. M. Karcher. 2015. Effect of rearing environment on bone growth of pullets. Poult. Sci. 94:502–511. Rylander, M. K., and E. G. Bolen. 1974. Analysis and comparison of gaits in whistling ducks (Dendrocygna). Wilson Bull. 86:237–245. Talaty, P. N., M. N. Katanbaf, and P. Y. Hester. 2010. Bone mineralization in male commercial broilers and its relationship to gait score. Poult. Sci. 89:342–348. Van Wyhe, R. C., P. Regmi, B. J. Powell, R. C. Haut, M. W. Orth, and D. M. Karcher. 2014. Bone characteristics and femoral strength in commercial toms: The effect of protein and energy restriction. Poult. Sci. 93:943–952. Van Wyhe, R. C., T. J. Applegate, M. S. Lilburn, and D. M. Karcher. 2012. A comparison of long bone development in historical and contemporary ducks. Poult. Sci. 91:2858–2865.
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Webster, A. B., B. D. Fairchild, T. S. Cummings, and P. A. Stayer. 2008. Validation of a three point gait-scoring system for field assessment of walking ability of commercial broilers. J. Appl. Poult. Res. 17:529–539. Weeks, C. A., T. D. Danbury, H. C. Davies, P. Hunt, and S. C. Kestin. 2000. The behaviour of broiler chickens and its modification by lameness. Appl. Anim. Behav. Sci. 67:111–125. Wideman, R. F., A. Al-Rubaye, D. Reynolds, D. Yoho, H. Lester, C. Spencer, J. D. Hughes, and I. Y. Pevzner. 2014. Bacterial chondronecrosis with osteomyelitis in broilers: influence of sires and straight-run versus sex-separate rearing. Poult. Sci. 93:1675– 1687. Williams, B., D. Waddington, D. H. Murray, and C. Farquharson. 2004. Bone strength during growth: Influence of growth rate on cortical porosity and mineralization. Calcif. Tissue Int. 74:236– 245. Zhong, Z., M. Muckley, S. Agcaoglu, M. E. Grisham, H. Zhao, M. Orth, M. S. Lilburn, O. Akkus, and D. M. Karcher. 2012. The morphological, material-level, and ash properties of turkey femurs from 3 different genetic strains during production. Poult. Sci. 91:2736–2746.
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Department of Animal Science, Michigan State University, East Lansing, MI; and † Department of Animal Sciences, Purdue University, West Lafayette, IN
ABSTRACT The rapid growth meat birds, including ducks, undergo requires skeletal integrity; however, fast growth may not be conducive to adequate bone structure. A relationship likely exists between skeletal changes and duck mobility. Reduced mobility in meat ducks may have impacts on welfare and production. This study examined the relationships among gait score, bone parameters, and hip angle. Commercial Pekin ducks, ages 14 d (n = 100), 21 d (n = 100), and 32 d (n = 100) were weighed and gait scored with a 3-point gait score system by an observer as they walked over a Tekscan gait analysis system. Gait was scored as GS0, GS1, or GS2 with a score of GS0 defined as good walking ability and a score of GS2 as poorest walking ability. Ducks were humanely euthanized, full body scanned using quantitative computed tomography (QCT), and the right femur and tibia were extracted. Leg bones were cleaned, measured, fat extracted, and ashed. QCT scans were rendered to create computer-
ized 3D models where pelvic hip angles and bone density were measured. Statistical analysis was conducted using PROC MIXED with age and gait score in the model. Body weight increased with age, but within an age, body weight decreased as walking ability became worse (P < 0.01). As expected, linear increases in tibia and femur bone width and length were observed as the ducks aged (P < 0.01). Right and left hip angle increased with duck age (P < 0.01). Additionally, ducks with a GS2 had wider hip angles opposed to ducks with a GS0 (P < 0.01). Bone density increased linearly with both age and gait score (P < 0.05). Femur ash content was lowest in 32-day-old ducks and ducks with GS1 and GS2 (P < 0.0001). Tibia ash content increased with age, but decreased as gait score increased (P < 0.001). The observation that right hip angle changed with gait scores merits further investigation into the relationship between duck mobility and skeletal changes during growth.
Key words: Pekin duck, gait score, bone ash, tibia, femur 2015 Poultry Science 94:1060–1067 http://dx.doi.org/10.3382/ps/pev050
INTRODUCTION Broiler chickens and turkeys are more commonly studied with less attention given to ducks. Irrespective of the species, meat birds have been genetically selected for breast yield resulting in an increased body weight that puts stress on the immature skeleton and can cause a variety of skeletal deformities and disorders (Lilburn, 1994; Brickett et al., 2007). Some of these bone abnormalities include tibial dyschondroplasia, osteomyelitis, bone fractures, and abnormal bone deformation (Orth and Cook, 1994; Charuta et al., 2011; Wideman et al., 2014). These disorders can lead to poor gait, lameness, and eventual culling from the population, resulting in poor animal well-being and product loss. Gait has been studied at length in broilers and turkeys using multiple gait scoring systems (Abourachid, 1991; Kestin et al., 1992; Webster et al., C 2015 Poultry Science Association Inc. Received September 3, 2014. Accepted December 3, 2014. 1 Corresponding author: [email protected]
2008). Kestin et al. (1992) developed a gait scoring system that was modified and adapted for use in ducks (Jones and Dawkins, 2010; O’Driscoll and Broom, 2011). Karcher et al. (2013) reported concern over the accurate assessment using the Jones and Dawkins (2010) modified duck gait scoring system due to the possibility of the natural fear response masking lameness. Additionally, the differences in musculoskeletal development and gait in ducks compared to chickens and turkeys raises concerns over the method’s appropriateness. Therefore, there is a need for research that explores the accuracy of the system, for example by assessing the relationship between gait score and physiological parameters. Sound structural conformation is a main contributor to successful locomotion and poor conformation may be conducive to lameness in ducks. To date only a few studies have attempted to address and quantify the relationships between gait and skeletal structural characteristics in ducks. The duck is considered to be a nonspecialist walker with a suboptimal walking gait. Compared to the gait of specialist walkers, the waddle
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has a high cost of locomotion as well as alterations in biomechanics. In order to waddle the duck must shift, tilt, and rotate its body to bring the center of mass over the stance leg (Nudds et al., 2010). Rylander and Bolen (1974) conducted a study comparing gait alterations in different species of whistling ducks. The cursorial species, adapted for running, had a greater hip angle and less angular displacement than the swimming species. This is likely a reflection of evolutionary adaptations to different habitats. Therefore, changes in the angular displacement of the hip were reflected as a change in gait. Skeletal assessment, including bone angulation, can be accomplished through computed tomography (CT), (Korver et al., 2004; Van Wyhe et al., 2014; Regmi et al., 2015) bone ashing (Brickett et al., 2007; Van Wyhe et al., 2012; Zhong et al., 2012), and physical observation. These methods allow measurements of morphological and skeletal parameters to determine what parameters may influence changes in walking ability. The purpose of our study was to evaluate the correlations between walking ability and skeletal parameters to determine whether alterations in hip angle, leg length, and bone characteristics have an impact on walking ability in commercial Pekin ducks.
MATERIALS AND METHODS All procedures were approved by the Institutional Animal Care and Use Committee of Michigan State University. On-farm data was collected on commercial duck farms located in northern Indiana. As part of a larger gait study, the walking abilities of 966 commercial Pekin ducks were assessed at 13 to 14 (14 d; 248 ducks), 20 to 21 (21 d; 350 ducks) and 30 to 32 (31 d; 368 ducks) d age. The ducks were selected from across 11 flocks housed in 7 different barns. Makagon et al. describes in detail the setup for assessing gait and descriptions for each gait score category. In order to have a balanced data set, ducks with each gait score were targeted and therefore, the data set does not mimic the distribution of each gait score in the population. Briefly, ducks were weighed, gender-identified, and walked through a tunnel containing a Tekscan gait analysis pad (Tekscan HRV2 High Resolution Animal Walkway System, Tekscan, Inc., South Boston, MA) to collect foot pad pressure, gait cadence, and velocity data. The ducks were videotaped from the anterior as they waddled through the tunnel. Simultaneously, a trained observer assigned each duck a gait score from “0” (GS0; best gait) to “2” (GS2; poor gait). A subsample of ducks was selected from the larger sample for skeletal analysis. To ensure that a representative sample of ducks with the 3 gait score categories was assessed, a minimum of 10 ducks with each score was selected from each age to be analyzed for skeletal parameters. An additional 80 ducks per age group were randomly selected for a total of 100 ducks per age (Table 1). These ducks
Table 1. Sample size distribution of ducks analyzed for each age by gait combination. Gait Score Age (d)
0
1
2
Total (n)
14 21 32
37 33 37
35 33 30
28 34 33
100 100 100
were CO2 euthanized, tagged for identification, placed on ice, and transported to Michigan State University for further analysis. All ducks were placed on their backs in dorsal recumbency with their legs out straight to rigor.
Computed Tomography and Necropsies Full-body scans of the ducks were done using a 16slice, GE Brightspeed quantitative computed tomography (QCT) scanner (General Electric Healthcare, Princeton, NJ) at the Michigan State University Veterinary Teaching Hospital. All ducks were allowed to go through rigor mortis in the same position prior to QCT scanning. Ducks were laid on the scanner board positioned in dorsal recumbency and scanned with a calibration phantom (Image Analysis, Inc., Columbia, KY) containing various concentrations of calcium hydroxyapatite. Bone lengths, bone density, leg length, and hip angles were analyzed from the scans using Mimics Innovation Software version 16.0 (Materialise, Plymouth, MI). Mimics Innovation Software measures density in Hounsfield units. During bone density analysis a linear regression line was created graphing the known values of mg Ca/cm3 , contained within the calibration phantom, against density of the phantom in Hounsfield units acquired from Mimics. The resulting linear equation was used to quantify the bone density measurements. The ends of the tarsometatarsus, tibia, and femur in each leg were located and the length from the distal end of the tarsometarasus to the distal end of the femur was measured. Then the distance from the distal end of the femur to the acetabulum was measured. Total leg length was measured as a summation of the length of the long bones plus the joint space from the acetabulum to the distal end of the tarsometatarsus. Hip angles were determined by measuring the midpoint of the distal end of the femur to the center of the acetabulum and then to the distal end of the pubis. The cross-sectional image slice at the midpoint of the right and left tibia and femur was measured to produce an average cortical bone density (CBD). Ducks were necropsied at the Diagnostic Center for Population and Animal Health where the right femur and tibia were removed. The leg bones were taken back to the lab and cleaned of surrounding muscles and soft tissues. The tibia and femur length were measured using a metric ruler, and bone width was determined with digital calipers (Model 68304, Pittsburgh, Camarillo,
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CA). The fibula was removed from the tibia and both tibia and femur were cut into pieces to enhance fat extraction, wrapped in cheesecloth, and placed into a soxhlet for ether extraction. After ether extraction, the bone pieces were weighed into crucibles for dry matter and ash. The bone pieces were dried at 105◦ C for 24 h in an American Scientific DN-81 constant temperature oven (Portland, OR). Bones were then placed in the ash oven (Thermolyne, 30400, Barnstead International, Dubuque, IA) at 600◦ C for 8 h. The ashed bone pieces were again weighed and ash percentage was determined.
Statistics Data were analyzed by using the PROC MIXED analysis of SAS 9.3 (SAS Institute, Cary, NC). The class variables were defined as age and gait. The main effects of age, gait score, and age by gait interactions were examined. Differences between means for age, gait score, and age by gait interactions were tested using Tukey’s adjustment with significance accepted at P < 0.05. In order to facilitate the interpretation of significant age by gait interactions, those data are presented graphically. Linear and quadratic contrasts were calculated for age and gait with significance considered at P < 0.05. Additionally, correlations were calculated between dependent variables to determine collinearity. Body weight was not used as a covariate for statistical analysis due to its strong correlation with the independent variables.
RESULTS AND DISCUSSION A duck’s ambulatory ability can have a negative impact on well-being and reduce producer profitability.
The reduced walking ability might translate to decreased growth potential or result in the duck being culled in severe cases. In broilers, Kestin et al. (1992) developed a scoring system to evaluate gait finding a relationship between body weight and leg weakness. Figure 1 presents the body weight of ducks at 14, 21, and 32 d age. As expected, body weight increased as the ducks aged (P < 0.01); however, the average body weight within a specific age decreased linearly as gait score worsened (P < 0.01). Talaty et al. (2010) reported broilers with poor walking ability, scores of 4 and 5 on a scale of 0 to 5, had decreased mobility and trouble accessing feeders and waterers resulting in lower body weights. However, Weeks et al. (2000) reported that broilers with poor walking ability made fewer visits to the feeder, but concomitantly increased the time spent at the feeder resulting in similar amounts of feed consumed to broilers with better walking ability. Therefore, the observation of a decreased average body weight of 0.5 kg at 32 d (Figure 1) between GS0 and the other gait scores could be a result of decreased mobility. This may have resulted in unsuccessful access to feed and water but this is a speculation, as resource usage was not evaluated. The Mimics Software provided analysis of bone structure in the 3D view to measure hip angulation as well as total leg length with main effects of age and gait score (Figure 2; Tables 2 and 3). In the current study, the use of QCT provided a novel approach, but also challenges. The ducks could not be scanned in a natural position, therefore a dorsal position with the legs and hips in a neutral position was chosen. However, the positioning of the duck on the CT scanner and human measurement error could alter the angles measured. The results revealed that right and left hip angle increased
Figure 1. Average body weight (kg) of 14, 21, and 32-day-old ducks by gait score. There was an overall age × gait score interaction (P < 0.01) and within each age group body weight decreased linearly as gait score increased (P < 0.01). Bars with differing letters within a given age designate differences between gait score P < 0.05.
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Figure 2. Three-dimentional image created from a QCT scan by Mimics Innovation Software version 16.0 (Materialise, Plymouth, MI) of the distal half of a duck’s skeleton.
with duck age (Table 2; P < 0.03) and the calculated difference between right and left hip angles increased from 0.33 degrees for ducks with GS0 to 3.04 degrees for ducks with GS2 (Table 3; P < 0.005). A main effect interaction was observed for right hip angle finding ducks within an age with gait scores of 1 and 2 had wider hip angles opposed to ducks with a gait score of 0 (Figure 3, P = 0.03). Rylander and Bolen (1974) conducted gait analysis of four different species of whistling ducks and showed differences in the angular displacement of the hip. In the
aforementioned study, hip angulation was measured using a series of 2D still images and measurements from preserved specimens to estimate bone length and position. Rylander and Bolen (1974) used the anterior ilium, acetabulum, and femur to look at hip angle because they were interested in how hip angle was affected by changes in vertical posture. In the current study, the focus was placed on how the walking ability is affected by hip angle, therefore it was important to include leg abduction so the distal pubis was used in place of the ilium to create the hip angle. Additionally, with the
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ROBISON ET AL. Table 2. Commercial Pekin duck skeletal parameter means at 3 different ages during a production period. Age Variable
14 d
Source of Variation
21 d
(P-value)1
32 d
Femur Dry weight (g) Ash (%) Length (cm) Width (mm)
1.28 47.52 4.88 4.89
± ± ± ±
0.05c 0.31a 0.04c 0.06c
2.28 48.30 5.92 5.94
± ± ± ±
0.05b 0.31a 0.04b 0.06b
3.85 46.36 6.90 6.90
± ± ± ±
0.05a 0.3b 0.04a 0.06a
< 0.0001 < 0.0001 < 0.0001 < 0.0001
Tibia Dry weight (g) Ash (%) Length (cm) Width (mm)
2.08 49.66 7.83 4.64
± ± ± ±
0.08c 0.34a 0.07c 0.07c
3.94 50.93 9.54 5.74
± ± ± ±
0.08b 0.34b 0.07b 0.07b
6.65 51.63 11.24 7.16
± ± ± ±
0.08a 0.34b 0.07a 0.07a
< 0.0001 0.0002 < 0.0001 < 0.0001
Hip angle (degree) Right Left Leg length (cm) Right Left Density (mg Ca/cm3 ) Right femur Left femur Right tibia Left tibia 1
71.52 ± 1.16b 69.56 ± 1.24b
72.98 ± 1.14a,b 71.18 ± 1.22a,b
75.79 ± 1.16a 75.18 ± 1.24a
0.03 0.005
17.71 ± 0.14c 17.58 ± 0.14c
20.61 ± 0.14b 20.63 ± 0.14b
23.75 ± 0.14a 23.79 ± 0.14a
< 0.0001 < 0.0001
± ± ± ±
< 0.0001 < 0.0001 < 0.0001 < 0.0001
460.90 451.59 435.35 433.95
± ± ± ±
10.14c 10.30b 11.06c 11.24c
501.74 518.82 482.35 491.97
± ± ± ±
10.07b 10.30a 10.99b 11.73b
552.21 540.90 550.80 541.75
10.29a 10.38a 11.10a 11.96a
Age main effect P-value. Different superscripts in a row designate significant differences between ages; P < 0.05.
a–c
Table 3. Commercial Pekin duck skeletal parameter means of 3 different gait scores assessed at 14, 21, and 32 d during a production period. Gait Score Variable
0
1
Source of Variation (P-value)1
2
Femur Dry weight (g) Ash (%) Length (cm) Width (mm)
2.48 48.63 5.92 5.92
± ± ± ±
0.04 0.30a 0.04 0.06
2.49 46.93 5.93 5.88
± ± ± ±
0.05 0.31b 0.04 0.06
2.43 46.61 5.84 5.94
± ± ± ±
0.05 0.32b 0.041 0.062
0.70 < 0.0001 0.24 0.77
Tibia Dry weight (g) Ash (%) Length (cm) Width (mm)
4.36 51.61 9.66 5.95
± ± ± ±
0.07 0.33a 0.07a 0.07
4.14 50.76 9.54 5.73
± ± ± ±
0.08 0.34a,b 0.07a,b 0.07
4.17 49.84 9.40 5.87
± ± ± ±
0.08 0.35b 0.07b 0.08
0.09 0.002 0.03 0.12
Hip angle (degree) Right Left
69.89 ± 1.12b 69.48 ± 1.20b
72.36 ± 1.16b 71.30 ± 1.25a,b
78.29 ± 1.19a 75.14 ± 1.26a
< 0.001 0.005
Leg length (cm) Right Left
21.14 ± 0.13a 21.14 ± 0.14a
20.58 ± 0.14b 20.59 ± 0.14b
20.35 ± 0.14b 20.26 ± 0.15b
0.0002 < 0.0001
± ± ± ±
0.005 0.0002 0.06 0.0027
Density (mg Ca/cm3 ) Right femur Left femur Right tibia Left tibia 1
479.93 476.89 474.95 463.25
± ± ± ±
9.76b 9.90b 10.59 11.24b
508.27 497.73 482.93 484.55
± ± ± ±
10.29a,b 10.46b 11.19 11.73a,b
526.23 536.69 510.63 519.87
10.44a 10.58a 11.37 11.96a
Gait main effect P-value. Different superscripts in a row designate significant differences between gait scores; P < 0.05.
a,b
ducks in a dorsal recumbancy position the angle using the ilium would have been distorted by positioning. Campbell et al. (2014) reported that in Pekin ducks metatarsal adduction was greater in the right pelvic limb compared to the left especially at 28 d; however, all ducks showed signs of metatarsal adduction suggest-
ing that it may be normal. Duff (1984) reported that turkeys with severe degenerative hip disease walked with an abnormal gait and stood and walked with abducted limbs possibly as a result of the disease. Biomechanical analysis of avian locomotion in guinea fowl demonstrated that a small change in the long angle
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Figure 3. Right hip angle (deg) of 14, 21, and 32-day-old ducks by gait score. There was an overall age × gait score interaction (P < 0.05) and within each age group hip angle increased linearly as gait score increased (P < 0.01). Bars with differing letters within a given age designate differences between gait score P < 0.05.
rotation of the hip could result in a relatively large distal displacement of the lower limb (Kambic et al., 2014). Hip angle in the current study was measured while the duck was in dorsal recumbency, an atypical position; however, if the changes in gait were chronic then alterations in musculature may also have occurred allowing measurable differences even in an atypical position. In future studies, it would be interesting to take still photos of the bird’s stance to compare to the 3D images from the CT scans. The increased hip angle observed in the current study might suggest increased metatarsal abduction resulting in a reluctance to rotate the leg completely under the center of mass during the stance phase. In addition to a change in the swing path of the leg, hip abduction widens the stance of the bird, which may alleviate pressure on an injured or sore limb. This would require further investigation. Leg length was measured as a summation of the length of the long bones plus the joint space from the acetabulum to the distal end of the tarsometatarsus. The joint space inclusion in measuring leg length would account for inflammation and swelling. In a human study on knee osteoarthritis, leg length was measured from the femoral head to the distal end of the tibia. In that study, patients with a leg length difference of 1 cm or greater had a 53% higher chance of having radiographic knee osteoarthritis in the shorter leg (Harvey, 2010). Right and left leg lengths were increased with duck age (Table 2; P < 0.0001). Conversely, the leg lengths decreased with increasing gait score (Table 3; P < 0.002). The decreasing leg length associated with gait score might be due to a smaller size of the bird, or be reflective of a fractured and remodeled tibia. During the 3D analysis, researchers observed that some leg
bones had remodeled fractures and that a large percentage of the ducks had tibias with a noticeable wave to the diaphyseal region; however, this information was not quantified. The tibia itself remained straight, but the cortical bone was modeled to give a wavy look to the bone. The rendering, or creation of the 3D image, of the bone may have had an overall impact on leg length, but when the femur and tibia were measured, length and width increased with age (Table 2; P < 0.0001) while tibia length decreased with increasing gait score (Table 3; P < 0.02). Therefore, the changes observed in leg length between 0 and 2 gait scored ducks were likely not impacted by the rendering. Rapid growth rate in meat birds has been suggested to be the main contributor to inadequate bone quality (Williams et al., 2004). Bone quality consists of the architectural organization as well as the organic and mineral matrices (Rath et al., 2000). Bone ash is a measure of the mineral content of the bone, primarily consisting of Ca and P. The inorganic matrix constitutes 60 to 70% of the bone weight providing bone weight and strength (Rath et al., 2000). The ash content of the femur was lowest in 32 d old ducks and ducks with gait scores of 1 and 2 (Tables 2, 3; P < 0.0001). Tibia ash content increased with age, but decreased as gait score became worse (Tables 2, 3; P < 0.001). A recent publication compared the bone ash of duck femurs and tibias from years 2010 and 1993 flocks (Van Wyhe et al., 2012). Although bone ash is reported as epiphyseal and diaphyseal ash, whole bone ash could be estimated as the average between the 2 measurements. Van Wyhe et al. (2012) reported tibia ash at 60% in the tibial diaphysis and 37% in the epiphysis, averaging to approximately 48.5% in 32-day-old year 2010 ducks, which is comparable to the 51% reported in the current study.
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Similarly, the femur ash measurement would average to approximately 49% in 32-day-old year 2010 ducks, which compares to the 46% reported in the current study. In addition to bone mineral content, bone density, defined as the mass of material per volume of bone (Rath et al., 2000), also provides valuable information on the quality of bone as it mirrors the status of bone health (Rath et al., 2000). Computed tomography has previously been used to determine volumetric bone mineral density (vBMD) and content in bones from turkeys and ducks (Charuta et al., 2012; Charuta and Cooper, 2012). In the current study, average bone density was measured at the midpoint of the tibia or femur in both the right and left leg. As expected, all density measurements increased linearly as the ducks aged (Table 2; P < 0.01). Table 3 reports the bone density for each gait score finding that as gait score increases so does the density (P < 0.005). This would suggest that as the duck ages the leg bones begin to undergo bi-lateral changes in bone density likely due to alterations in gait. Research conducted in French Pekin ducks with a 56 d slaughtering maturity reported higher vBMD at the middle of the diaphysis of the tibiotarsal bone at both 14 and 28 d (∼625 mg/cm3 ; Charuta et al., 2012). Fourteen-day-old ducks had vBMD of 435 mg/cm3 and 32-day-old ducks had a vBMD of 540 mg/cm3 (Table 2). The ducks in the current study have been selected for a 36 d slaughtering maturity and were heavier than the French ducks at both time points. Therefore, the authors speculate that the combination of increased body weight coupled with reduced vBMD could predispose bone to fractures as the duck reaches its physiological limit on the quantity and quality of bone it can produce. The ability to create 3D models of the skeleton from the QCT scans of an intact duck provides the opportunity to measure joint angulation and skeletal structure, and offers insight into the skeletal development of the Pekin duck. The rapid growth Pekin ducks experience in a short time frame requires sufficient skeletal integrity to ensure mobility. The increase in body weight, leg length, and bone density was expected since the ducks are growing. The interesting observations made between a decreased leg length, increased bone density, and increased right hip angle related to higher gait scores require further examination of these specific variables. Further studies involving muscular development, skeletal health (e.g. osteomyelitis), and skeletal injury (e.g., fractures) also need to be conducted to determine the impact on gait score. A refined understanding of the complex relationship between management practices, skeletal parameters, and gait score will then allow for duck well-being to be better understood.
ACKNOWLEDGMENTS We gratefully acknowledge Maple Leaf Farms, Inc. (Leesburg, IN) for generously providing resources for this study, and particularly Michael Turk and Daniel
Shafer for supporting this study. We thank Chad Risch (Maple Leaf Farms, Inc.) and Stephanie Robles (Purdue University) for overseeing and assisting with onfarm data collection. For assistance in various phases of data collection we thank: Prafulla Regmi, Robert Van Wyhe, Kailynn Van de Water, Natalie Smith, Diondra Voisch, and Lachelle Devoe from Michigan State University; and Luna KC, Kayla Winemiller, and Danyi Ma from Purdue University.
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